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. 2025 May;116(5):1239-1254.
doi: 10.1111/cas.70001. Epub 2025 Feb 13.

Mefloquine Suppresses Metastasis in Renal Cell Carcinoma Through Targeting SPC25

Affiliations

Mefloquine Suppresses Metastasis in Renal Cell Carcinoma Through Targeting SPC25

Yongbo Wang et al. Cancer Sci. 2025 May.

Abstract

Renal cell carcinoma (RCC) is the third most common malignant tumor in the urinary system, often presenting with distant metastases at diagnosis. Approximately one-quarter of patients undergoing nephrectomy experience distant recurrence. Despite the recent advancements in combination-targeted and immune checkpoint inhibitor therapies, the development of new therapeutic strategies and the identification of biomarkers for metastatic risk remain crucial. The study found that high SPC25 expression is closely associated with poor clinical outcomes, and knocking down SPC25 significantly inhibits tumor cell proliferation and migration. Non-targeted metabolomics analysis also revealed that SPC25 knockdown reduces tumor cell activity, resulting in a low-invasive state. Additionally, this study utilized high-throughput molecular docking to screen small molecule drugs targeting SPC25, aiming to find drugs that inhibit RCC metastasis. The research discovered that mefloquine, at concentrations that do not significantly kill tumor cells, can markedly inhibit RCC metastasis. It was the first to report that mefloquine achieves its anti-metastatic effects by binding to SPC25 and inhibiting epithelial-mesenchymal transition. These results suggest that SPC25 has the potential to serve as an early biomarker for metastatic risk in RCC and highlight a novel strategy where mefloquine inhibits RCC metastasis through SPC25 binding, offering new avenues to improve the prognosis of RCC patients.

Keywords: SPC25; mefloquine; renal cell carcinoma; tumor migration.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

FIGURE 1
FIGURE 1
SPC25 Expression and Prognostic Significance in RCC. (A) GSE47352 microarray composition. (B) Volcano plot of mRCC versus non‐mRCC DEGs (p < 0.05, FC ≥ 2). (C) Venn diagram of DEGs overlap with epigenetic regulation‐related genes. (D) Survival curve indicating poorer prognosis with high SPC25 expression (n = 552). (E, F) Higher SPC25 expression in TCGA tumor tissues versus adjacent non‐tumor tissues (p < 0.001), shown by paired and unpaired analyses. (G) Elevated SPC25 in various tumors versus normal tissues. (H) IHC analysis of SPC25 in tissue microarray (n = 154), emphasizing increased tumor expression. (I, J) Histological scoring via ImageJ for paired (n = 44) and unpaired (normal [n = 110] versus tumor [n = 44]) samples, showing significant differences (p < 0.05, p < 0.01). (K) Survival curves of the 61 surveyed patients. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.
FIGURE 2
FIGURE 2
Functional Enrichment, GSVA, Mutation Profile, and Immune Cell Distribution in the Tumor Microenvironment (TME). (A) BP (biological process). (B) MF (molecular function). (C) CC (cellular component). (D) KEGG functional enrichment. (E) GSVA showing pathway differences between groups. (F) mutation profile of RCC samples with high SPC25 expression from TCGA. (G, H) Immune cell composition in TCGA tumor samples analyzed by CIBERSORT. (I) Comparison of immune cell distribution between high and low SPC25 expression groups.
FIGURE 3
FIGURE 3
The role of SPC25 in RCC cell phenotype. (A) Western blot detection of SPC25 expression in Caki‐1, Caki‐2, ACHN, and 786‐O RCC cell lines to select experimental cells. (B) Confirmation of SPC25 knockdown in Caki‐1 and Caki‐2 cells by Western blot, showing significant reduction in SPC25 protein (p < 0.001, p < 0.01). (C) CCK8 assay showed significantly reduced proliferation in the knockdown group (p < 0.0001). (D) Flow cytometry analysis revealing changes in the cell cycle between control and knockdown groups. (E) Flow cytometry indicating a significantly higher proportion of apoptotic cells in the knockdown group (p < 0.0001, p < 0.01). The Annexin V‐FITC positive cells (Q2, Q3) represented the sum of apoptotic cells. (F) Scratch assay showed significantly lower migration rates in the knockdown group (p < 0.001). (G) Migration and invasion assays demonstrating significant inhibition of these processes in the knockdown group (p < 0.001, p < 0.01). (H) Western blot analysis of Snail, Vimentin, and E‐cadherin protein levels. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.
FIGURE 4
FIGURE 4
Non‐targeted metabolomic analysis of SPC25 impact on RCC cell metabolism. (A) PCA score plot for shCtrl (green), shSPC25 (pink), and QC (blue) groups. QC stands for quality control samples. (B) OPLS‐DA score plot for shCtrl (green) and shSPC25 (pink) groups. (C, D) Volcano plots of metabolites in RCC cells under positive and negative ion modes. (E, F) KEGG pathway enrichment of selected differential metabolites (p < 0.05, |FC| > 1.2, VIP ≥ 1). (G, H) Heatmaps of the top 30 differential metabolites.
FIGURE 5
FIGURE 5
Screening for potential therapeutic drugs targeting SPC25. (A) Molecular models of ZINC000003874467 (Nafamostat) and ZINC000003874185 (Mefloquine) binding to SPC25. (B) Molecular surface representation of the protein‐ligand complex from docking studies, with the protein in gray and the ligand in green, highlighting the binding site. (C—E) Cell viability measurements after 24‐h treatment of RCC cells with drugs identified through virtual screening. (F—K) Cell viability of Caki‐1, Caki‐2, Caki‐1 shSPC25, Caki‐2 shSPC25, and MDCK after 24 h of mefloquine treatment. (L) CETSA analysis to determine the affinity of mefloquine for SPC25, with Western Blot indicating SPC25 thermal stability. (M) Thermal melting curves of SPC25.
FIGURE 6
FIGURE 6
Effects of Mefloquine on the motility, migration, and cell cycle of RCC cells. (A, B) Scratch assays of Caki‐1 and Caki‐2 cells 24 h after treatment with mefloquine, showing a dose‐dependent decrease in cell motility. (C, D) Migration and invasion assays under the same conditions, demonstrating a dose‐dependent decrease in cell migration capabilities. (E, F) Cell cycle analysis indicating a dose‐dependent increase in the G2/M phase ratio relative to the S phase. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.
FIGURE 7
FIGURE 7
Effect of mefloquine on apoptosis of RCC cells and animal experiments. (A) Dose‐dependent increase in apoptosis rate of RCC cells treated with mefloquine. The Annexin V‐FITC positive cells (Q2, Q3) represented the sum of apoptotic cells. (B) Western blots showing mefloquine's dose‐dependent effects on SPC25, Snail, Vimentin, and E‐cadherin protein levels. (C) Caki‐1 tumor‐bearing nude mice were administered glucose, mefloquine (25 mg/kg, orally), and sunitinib (20 mg/kg, orally) daily. (D) Final tumor size, (E) changes in tumor volume, (F) relative change in tumor volume, and (G) changes in body weight of nude mice were assessed after 15 days. Tumor sizes were measured with calipers, and volumes were calculated using the formula: V = (length × width2)/2. The levels of key biochemical markers in the serum of nude mice after 15 days of treatment, including (H) ALT, (I) AST, (J) BUN, and (K) UA. (L) HE (Hematoxylin and Eosin) staining results of liver and lung tissue sections. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.
FIGURE 8
FIGURE 8
Research approach of this study.

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